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added model card for codeswitch-spaeng-sentiment-analysis-lince (#6727)

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* added model card for codeswitch-spaeng-sentiment-analysis-lince model also update other model card

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* Update README.md
This commit is contained in:
Sagor Sarker
2020-08-27 03:26:32 +06:00
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parent e10fb9cbe6
commit cc4ba79f68
8 changed files with 145 additions and 27 deletions
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23
model_cards/sagorsarker/codeswitch-hineng-lid-lince/README.md
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@@ -2,19 +2,35 @@
language: language:
- hi - hi
- en - en
datasets:
- LinCE
license: "MIT"
tags:
- codeswitching
- hindi-english
- language-identification
--- ---
# codeswitch-hineng-lid-lince # codeswitch-hineng-lid-lince
This is a pretrained model for **language identification** of `hindi-english` code-mixed data used from [LinCE](https://ritual.uh.edu/lince/home) This is a pretrained model for **language identification** of `hindi-english` code-mixed data used from [LinCE](https://ritual.uh.edu/lince/home)
This model is trained for this below repository.
[https://github.com/sagorbrur/codeswitch](https://github.com/sagorbrur/codeswitch)
To install codeswitch:
```
pip install codeswitch
```
## Identify Language ## Identify Language
* Method-1 * **Method-1**
```py ```py
from transformers import AutoTokenizer, AutoModelForTokenClassification from transformers import AutoTokenizer, AutoModelForTokenClassification, pipeline
tokenizer = AutoTokenizer.from_pretrained("sagorsarker/codeswitch-hineng-lid-lince") tokenizer = AutoTokenizer.from_pretrained("sagorsarker/codeswitch-hineng-lid-lince")
@@ -25,10 +41,9 @@ lid_model("put any hindi english code-mixed sentence")
``` ```
* Method-2 * **Method-2**
```py ```py
# !pip install codeswitch
from codeswitch.codeswitch import LanguageIdentification from codeswitch.codeswitch import LanguageIdentification
lid = LanguageIdentification('hin-eng') lid = LanguageIdentification('hin-eng')
text = "" # your code-mixed sentence text = "" # your code-mixed sentence

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model_cards/sagorsarker/codeswitch-hineng-ner-lince/README.md
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@@ -2,6 +2,13 @@
language: language:
- hi - hi
- en - en
datasets:
- LinCE
license: "MIT"
tags:
- codeswitching
- hindi-english
- ner
--- ---
# codeswitch-hineng-ner-lince # codeswitch-hineng-ner-lince
@@ -17,13 +24,13 @@ To install codeswitch:
pip install codeswitch pip install codeswitch
``` ```
## Identify Language ## Name Entity Recognition of Code-Mixed Data
* Method-1 * **Method-1**
```py ```py
from transformers import AutoTokenizer, AutoModelForTokenClassification from transformers import AutoTokenizer, AutoModelForTokenClassification, pipeline
tokenizer = AutoTokenizer.from_pretrained("sagorsarker/codeswitch-hineng-ner-lince") tokenizer = AutoTokenizer.from_pretrained("sagorsarker/codeswitch-hineng-ner-lince")
@@ -35,7 +42,7 @@ ner_model("put any hindi english code-mixed sentence")
``` ```
* Method-2 * **Method-2**
```py ```py
from codeswitch.codeswitch import NER from codeswitch.codeswitch import NER

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model_cards/sagorsarker/codeswitch-hineng-pos-lince/README.md
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@@ -2,6 +2,13 @@
language: language:
- hi - hi
- en - en
datasets:
- LinCE
license: "MIT"
tags:
- codeswitching
- hindi-english
- pos
--- ---
# codeswitch-hineng-pos-lince # codeswitch-hineng-pos-lince
@@ -17,13 +24,13 @@ To install codeswitch:
pip install codeswitch pip install codeswitch
``` ```
## Identify Language ## Part-of-Speech Tagging of Hindi-English Mixed Data
* Method-1 * **Method-1**
```py ```py
from transformers import AutoTokenizer, AutoModelForTokenClassification from transformers import AutoTokenizer, AutoModelForTokenClassification, pipeline
tokenizer = AutoTokenizer.from_pretrained("sagorsarker/codeswitch-hineng-pos-lince") tokenizer = AutoTokenizer.from_pretrained("sagorsarker/codeswitch-hineng-pos-lince")
@@ -34,7 +41,7 @@ pos_model("put any hindi english code-mixed sentence")
``` ```
* Method-2 * **Method-2**
```py ```py
from codeswitch.codeswitch import POS from codeswitch.codeswitch import POS

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model_cards/sagorsarker/codeswitch-nepeng-lid-lince/README.md
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@@ -2,6 +2,13 @@
language: language:
- ne - ne
- en - en
datasets:
- LinCE
license: "MIT"
tags:
- codeswitching
- nepali-english
- language-identification
--- ---
# codeswitch-nepeng-lid-lince # codeswitch-nepeng-lid-lince
@@ -19,11 +26,11 @@ pip install codeswitch
## Identify Language ## Identify Language
* Method-1 * **Method-1**
```py ```py
from transformers import AutoTokenizer, AutoModelForTokenClassification from transformers import AutoTokenizer, AutoModelForTokenClassification, pipeline
tokenizer = AutoTokenizer.from_pretrained("sagorsarker/codeswitch-nepeng-lid-lince") tokenizer = AutoTokenizer.from_pretrained("sagorsarker/codeswitch-nepeng-lid-lince")
@@ -34,7 +41,7 @@ lid_model("put any nepali english code-mixed sentence")
``` ```
* Method-2 * **Method-2**
```py ```py
from codeswitch.codeswitch import LanguageIdentification from codeswitch.codeswitch import LanguageIdentification

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model_cards/sagorsarker/codeswitch-spaeng-lid-lince/README.md
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@@ -2,19 +2,35 @@
language: language:
- es - es
- en - en
datasets:
- LinCE
license: "MIT"
tags:
- codeswitching
- spanish-english
- language-identification
--- ---
# codeswitch-spaeng-lid-lince # codeswitch-spaeng-lid-lince
This is a pretrained model for **language identification** of `spanish-english` code-mixed data used from [LinCE](https://ritual.uh.edu/lince/home) This is a pretrained model for **language identification** of `spanish-english` code-mixed data used from [LinCE](https://ritual.uh.edu/lince/home)
This model is trained for this below repository.
[https://github.com/sagorbrur/codeswitch](https://github.com/sagorbrur/codeswitch)
To install codeswitch:
```
pip install codeswitch
```
## Identify Language ## Identify Language
* Method-1 * **Method-1**
```py ```py
from transformers import AutoTokenizer, AutoModelForTokenClassification from transformers import AutoTokenizer, AutoModelForTokenClassification, pipeline
tokenizer = AutoTokenizer.from_pretrained("sagorsarker/codeswitch-spaeng-lid-lince") tokenizer = AutoTokenizer.from_pretrained("sagorsarker/codeswitch-spaeng-lid-lince")
@@ -25,10 +41,9 @@ lid_model("put any spanish english code-mixed sentence")
``` ```
* Method-2 * **Method-2**
```py ```py
# !pip install codeswitch
from codeswitch.codeswitch import LanguageIdentification from codeswitch.codeswitch import LanguageIdentification
lid = LanguageIdentification('spa-eng') lid = LanguageIdentification('spa-eng')
text = "" # your code-mixed sentence text = "" # your code-mixed sentence

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model_cards/sagorsarker/codeswitch-spaeng-ner-lince/README.md
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@@ -2,6 +2,13 @@
language: language:
- es - es
- en - en
datasets:
- LinCE
license: "MIT"
tags:
- codeswitching
- spanish-english
- ner
--- ---
# codeswitch-spaeng-ner-lince # codeswitch-spaeng-ner-lince
@@ -17,13 +24,13 @@ To install codeswitch:
pip install codeswitch pip install codeswitch
``` ```
## Identify Language ## Name Entity Recognition of Spanish-English Mixed Data
* Method-1 * **Method-1**
```py ```py
from transformers import AutoTokenizer, AutoModelForTokenClassification from transformers import AutoTokenizer, AutoModelForTokenClassification, pipeline
tokenizer = AutoTokenizer.from_pretrained("sagorsarker/codeswitch-spaeng-ner-lince") tokenizer = AutoTokenizer.from_pretrained("sagorsarker/codeswitch-spaeng-ner-lince")
@@ -35,7 +42,7 @@ ner_model("put any spanish english code-mixed sentence")
``` ```
* Method-2 * **Method-2**
```py ```py
from codeswitch.codeswitch import NER from codeswitch.codeswitch import NER

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model_cards/sagorsarker/codeswitch-spaeng-pos-lince/README.md
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@@ -2,6 +2,13 @@
language: language:
- es - es
- en - en
datasets:
- LinCE
license: "MIT"
tags:
- codeswitching
- spanish-english
- pos
--- ---
# codeswitch-spaeng-pos-lince # codeswitch-spaeng-pos-lince
@@ -17,13 +24,13 @@ To install codeswitch:
pip install codeswitch pip install codeswitch
``` ```
## Identify Language ## Part-of-Speech Tagging of Spanish-English Mixed Data
* Method-1 * **Method-1**
```py ```py
from transformers import AutoTokenizer, AutoModelForTokenClassification from transformers import AutoTokenizer, AutoModelForTokenClassification, pipeline
tokenizer = AutoTokenizer.from_pretrained("sagorsarker/codeswitch-spaeng-pos-lince") tokenizer = AutoTokenizer.from_pretrained("sagorsarker/codeswitch-spaeng-pos-lince")
@@ -34,7 +41,7 @@ pos_model("put any spanish english code-mixed sentence")
``` ```
* Method-2 * **Method-2**
```py ```py
from codeswitch.codeswitch import POS from codeswitch.codeswitch import POS

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model_cards/sagorsarker/codeswitch-spaeng-sentiment-analysis-lince/README.md Normal file
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@@ -0,0 +1,53 @@
---
language:
- es
- en
datasets:
- LinCE
license: "MIT"
tags:
- codeswitching
- spanish-english
- sentiment-analysis
---
# codeswitch-spaeng-sentiment-analysis-lince
This is a pretrained model for **Sentiment Analysis** of `spanish-english` code-mixed data used from [LinCE](https://ritual.uh.edu/lince/home)
This model is trained for this below repository.
[https://github.com/sagorbrur/codeswitch](https://github.com/sagorbrur/codeswitch)
To install codeswitch:
```
pip install codeswitch
```
## Sentiment Analysis of Spanish-English Code-Mixed Data
* **Method-1**
```py
from transformers import AutoTokenizer, AutoModelForSequenceClassification, pipeline
tokenizer = AutoTokenizer.from_pretrained("sagorsarker/codeswitch-spaeng-sentiment-analysis-lince")
model = AutoModelForSequenceClassification.from_pretrained("sagorsarker/codeswitch-spaeng-sentiment-analysis-lince")
nlp = pipeline('sentiment-analysis', model=model, tokenizer=tokenizer)
sentence = "El perro le ladraba a La Gatita .. .. lol #teamlagatita en las playas de Key Biscayne este Memorial day"
nlp(sentence)
```
* **Method-2**
```py
from codeswitch.codeswitch import SentimentAnalysis
sa = SentimentAnalysis('spa-eng')
sentence = "El perro le ladraba a La Gatita .. .. lol #teamlagatita en las playas de Key Biscayne este Memorial day"
result = sa.analyze(sentence)
print(result)
```